Road Network Generation from Dispersed Location Data
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Solution Overview
Problem
Current methods are inefficient and inaccurate in generating road networks using location data from vehicles and portable devices, due to dispersed and irregular data distribution, lack of topological information, and high data volume, making it difficult to create a complete and coherent road network.
Innovation Solution
A method and system that identify and refine target areas in a road network skeleton using trajectory information, combining image processing technologies to generate a road network skeleton quickly and accurately, and continuously update it with incremental trajectories, ensuring accuracy even with uneven location distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If location data is collected from multiple users traveling along specific routes, then the road network can be generated, but the data becomes dispersed and irregular making it difficult to generate accurate road networks
Solution Approach 1:
The patent segments the road network generation process into two distinct phases: skeleton generation from dispersed location data, and subsequent refinement of target areas using trajectory information. This segmentation allows the system to first create a basic structure from available data, then progressively improve accuracy by focusing computational resources on specific areas that need refinement, rather than attempting to process all data uniformly.
Solution Approach 2:
The patent performs preliminary generation of a road network skeleton before refinement. This preliminary structure provides a foundation that can be progressively improved. By establishing the basic road network framework first, the system creates a usable initial product that can then be enhanced through subsequent refinement operations on identified target areas.
2Ease of operation
If traditional methods are used to obtain road network information, then data can be obtained, but it requires purchasing data in lump or by use times which is inconvenient and inflexible
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically generates and updates road network information by processing location data from multiple sources. Instead of requiring users to manually purchase or request data, the system autonomously collects, processes, and maintains the road network database, making it freely accessible and continuously updated based on real-world usage patterns.
Solution Approach 2:
The patent creates a universal road network data system that serves multiple purposes and users simultaneously. The generated road network can be used for navigation, route planning, location-based services, and other applications. The system adapts to different user needs by continuously incorporating location data from various sources and refining the network based on actual usage patterns.
3Quantity of substance
If location data volume is considerable, then more complete road coverage can be achieved, but processing speed and efficiency are reduced
Solution Approach 1:
The patent divides the processing workload by separating skeleton generation from area refinement. The skeleton generation phase processes all location data to create a basic road network structure, while the refinement phase focuses computational resources on specific target areas. This segmentation enables parallel processing and prevents the system from being bottlenecked by attempting to process and refine all data uniformly.
Solution Approach 2:
The patent applies partial action by refining only specific target areas rather than the entire road network. The system identifies areas that need refinement based on the skeleton and selectively processes those regions using trajectory data. This approach achieves necessary accuracy in critical areas without the excessive computational cost of refining the entire network uniformly.
4Adaptability or versatility
If users provide location data voluntarily without pre-planned routes, then more data sources are available, but the data lacks basic topological information required for generating road networks
Solution Approach 1:
The patent performs preliminary generation of a road network skeleton that establishes basic topological structure from dispersed location data. This preliminary action creates the essential framework including road segments and intersections, even though the input data lacks explicit topological information. The skeleton serves as a foundation that encodes the necessary topological relationships.
Solution Approach 2:
The patent uses feedback mechanisms where the generated skeleton and refined road network are continuously improved using additional trajectory information. The system processes location data, generates or refines the road network, and uses the results to guide further data collection and processing. This iterative feedback loop progressively recovers and refines topological information that was not explicitly present in the original voluntary location data.
Data Source
AI summary
The present disclosure relates to a method and system for generating a road network. An embodiment of the present invention provides a method comprising: identifying a target area to be refined in a road network skeleton; and refining the target area using at least one trajectory associated with the target area to generate the road network. Another embodiment of the present invention provides a corresponding system.